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1

Create a Python file

touch basic_streaming.py
2

Add the following code to your Python file

basic_streaming.py
"""
This example demonstrates asynchronous streaming responses from a team.

The team uses specialized agents with financial tools to provide real-time
stock information with async streaming output.
"""

import asyncio

from agno.agent import Agent
from agno.models.openai import OpenAIChat
from agno.team.team import Team
from agno.tools.exa import ExaTools
from agno.utils.pprint import apprint_run_response

# Stock price and analyst data agent
stock_searcher = Agent(
    name="Stock Searcher",
    model=OpenAIChat("gpt-5-mini"),
    role="Searches the web for information on a stock.",
    tools=[
        ExaTools(
            include_domains=["cnbc.com", "reuters.com", "bloomberg.com", "wsj.com"],
            text=False,
            show_results=True,
            highlights=False,
        )
    ],
)

# Company information agent
company_info_agent = Agent(
    name="Company Info Searcher",
    model=OpenAIChat("gpt-5-mini"),
    role="Searches the web for information on a company.",
    tools=[
        ExaTools(
            include_domains=["cnbc.com", "reuters.com", "bloomberg.com", "wsj.com"],
            text=False,
            show_results=True,
            highlights=False,
        )
    ],
)

# Create team with async streaming capabilities
team = Team(
    name="Stock Research Team",
    model=OpenAIChat("gpt-5-mini"),
    members=[stock_searcher, company_info_agent],
    markdown=True,
    show_members_responses=True,
)


async def streaming_with_arun():
    """Demonstrate async streaming using arun() method."""
    await apprint_run_response(
        team.arun(input="What is the current stock price of NVDA?", stream=True)
    )


async def streaming_with_aprint_response():
    """Demonstrate async streaming using aprint_response() method."""
    await team.aprint_response("What is the current stock price of NVDA?", stream=True)


if __name__ == "__main__":
    asyncio.run(streaming_with_arun())

    # asyncio.run(streaming_with_aprint_response())
3

Create a virtual environment

Open the Terminal and create a python virtual environment.
python3 -m venv .venv
source .venv/bin/activate
4

Install libraries

pip install -U agno exa_py openai
5

Export your API keys

export OPENAI_API_KEY="your_openai_api_key_here"
export EXA_API_KEY="your_exa_api_key_here"
6

Run Team

python basic_streaming.py
7

Find All Cookbooks

Explore all the available cookbooks in the Agno repository. Click the link below to view the code on GitHub:Agno Cookbooks on GitHub